JP7209608B2 - Information processing device, program and information processing method - Google Patents

Description

The present invention relates to an information processing device, a program, and an information processing method.

2. Description of the Related Art In recent years, a surveillance system has been introduced in which a plurality of surveillance cameras are used to monitor a specific area such as the inside or entrance of a commercial facility as a surveillance area. In a monitoring system, it is preferable to efficiently arrange a plurality of monitoring cameras so that a wide range within a monitoring area can be monitored.

Patent Literature 1 describes an optimum placement search device using voxels. The optimum arrangement search device generates a voxel space by dividing the spatial model of the monitored area into voxels. Then, the optimum arrangement search device arranges a plurality of surveillance cameras in the voxel space, and counts the number of voxels captured by any of the arranged surveillance cameras, thereby obtaining an evaluation value of the arrangement. calculate. This optimum arrangement search device searches for the optimum arrangement by repeating the process of changing the arrangement of a plurality of surveillance cameras and calculating the evaluation values.

JP 2018-128961 A

In the conventional technique, the monitoring area is divided into voxels of the same shape and size, and the count value when one voxel can be imaged is also fixed to "1". For this reason, the conventional technique is inconvenient because it is impossible to set an area to be monitored intensively within the monitoring area.

Therefore, in the present invention, when a monitoring area is monitored using a plurality of imaging devices, the optimum arrangement of the plurality of imaging devices is determined in consideration of areas within the monitoring region that should be monitored intensively. aim.

An information processing apparatus according to a first aspect of the present invention includes a monitoring region setting unit that arranges a plurality of first voxels having a predetermined shape and size in a virtual monitoring region, and the monitoring region. an important monitoring area setting unit for setting an important monitoring area, which is an area to be intensively monitored; A process of calculating a score by changing either one and counting values obtained from the space in which the first voxels included in any of the plurality of imaging ranges of the plurality of imaging devices are arranged. and an optimum placement search unit that searches for placement of the plurality of imaging devices that maximizes the score under a predetermined condition by repeating the steps above, wherein the priority monitoring area setting unit is configured to search for the placement of the plurality of imaging devices in the priority monitoring area. by dividing each of the first voxels in the area to generate a plurality of second voxels; By counting the number of the second voxels located in the area outside the focused monitoring area, the value obtained from the space in which the first voxels are located is calculated. The score is calculated so as to be higher than the value obtained from the space obtained from the

An information processing apparatus according to a second aspect of the present invention includes a monitoring area setting unit that arranges a plurality of first voxels having a predetermined shape and size in a virtual monitoring area, and the monitoring area. an important monitoring area setting unit for setting an important monitoring area, which is an area to be intensively monitored; A process of calculating a score by changing either one and counting values obtained from the space in which the first voxels included in any of the plurality of imaging ranges of the plurality of imaging devices are arranged. by repeating the above, an optimal placement search unit for searching for placement of the plurality of imaging devices that maximizes the score under a predetermined condition; a score setting unit that generates a second voxel by setting a score for each of the planes , wherein the optimum placement search unit searches for any one of the plurality of imaging ranges within the important monitoring area A value corresponding to the score set for the included second voxels is counted, and outside the focused monitoring area, the number of the first voxels included in any of the plurality of imaging ranges is counted. The score is calculated by counting .

A program according to a first aspect of the present invention comprises: a monitoring region setting unit for arranging a plurality of first voxels having a predetermined shape and size in a monitoring region imagining a region to be monitored; an important monitoring area setting unit for setting an important monitoring area, which is an area to be monitored intensively; By changing at least one of them, a score is calculated by counting values obtained from a space in which the first voxels included in any of the plurality of imaging ranges of the plurality of imaging devices are arranged. By repeating the processing, it functions as an optimum placement search unit that searches for the placement of the plurality of imaging devices that maximizes the score under a predetermined condition, and the priority monitoring area setting unit sets the priority monitoring area. by dividing each of the first voxels in the area to generate a plurality of second voxels; by counting the number of the second voxels located outside the focused monitoring area, the value obtained from the space in which the first voxels are located within the focused monitoring area; The score is calculated so as to be higher than the value obtained from the calculated space .

A computer program according to a second aspect of the present invention comprises a monitoring region setting unit that arranges a plurality of first voxels having a predetermined shape and size in a virtual monitoring region that is an area to be monitored, and the monitoring region. an important monitoring area setting unit for setting an important monitoring area, which is an area to be monitored intensively; By changing at least one of them, a score is calculated by counting values obtained from a space in which the first voxels included in any of the plurality of imaging ranges of the plurality of imaging devices are arranged. an optimum arrangement search unit for searching for an arrangement of the plurality of imaging devices that maximizes the score under a predetermined condition by repeating the process; By setting the number of points for each of the planes, the optimum placement search unit functions as a point allocation setting unit that generates a second voxel, and the optimal placement search unit determines, within the important monitoring area, any one of the plurality of imaging ranges. A value corresponding to the score set for the included second voxels is counted, and outside the focused monitoring area, the number of the first voxels included in any of the plurality of imaging ranges is counted. The score is calculated by counting .

In the information processing method according to the first aspect of the present invention, the monitoring region setting unit arranges a plurality of first voxels having a predetermined shape and size in a virtual monitoring region to be monitored, and performs focused monitoring. An area setting unit sets an important monitoring area, which is an area to be monitored intensively, within the monitoring area, and an optimal placement searching unit selects at least a plurality of imaging devices virtually arranged in the monitoring area. Counting values obtained from a space in which the first voxels included in any of the plurality of imaging ranges of the plurality of imaging devices are arranged by changing at least one of the position and orientation of a part of them By repeating the process of calculating the score, the priority monitoring area setting unit searches for an arrangement of the plurality of imaging devices that maximizes the score under predetermined conditions, and the priority monitoring area setting unit by dividing each of the first voxels in the area to generate a plurality of second voxels; By counting the number of the second voxels located in the area outside the focused monitoring area, the value obtained from the space in which the first voxels are located is calculated. The score is calculated so as to be higher than the value obtained from the space obtained from the

In an information processing method according to a second aspect of the present invention, a monitoring region setting unit arranges a plurality of first voxels having a predetermined shape and size in a virtual monitoring region to be monitored, and performs focused monitoring. An area setting unit sets an important monitoring area, which is an area to be monitored intensively, within the monitoring area, and an optimal placement searching unit selects at least a plurality of imaging devices virtually arranged in the monitoring area. Counting values obtained from a space in which the first voxels included in any of the plurality of imaging ranges of the plurality of imaging devices are arranged by changing at least one of the position and orientation of a part of them By repeating the process of calculating the score by doing so, the arrangement of the plurality of imaging devices that maximizes the score under predetermined conditions is searched, and the point allocation setting unit determines whether each generating a second voxel by setting a score to each of a plurality of planes of the first voxel, and the optimum placement search unit selects any one of the plurality of imaging ranges within the focused monitoring area outside the focused monitoring area, the number of the first voxels included in any one of the plurality of imaging ranges The score is calculated by counting .

According to one or more aspects of the present invention, when monitoring a monitoring area using a plurality of imaging devices, an area to be monitored intensively within the monitoring region is taken into consideration to optimize the plurality of imaging devices. Placement can be determined.

1 is a block diagram schematically showing a configuration of an information processing device according to Embodiments 1, 2 and 5; FIG. FIG. 4 is a perspective view showing an example of a monitoring area; (A) and (B) are schematic diagrams for explaining a first example of a method of setting an important monitoring area. (A) and (B) are schematic diagrams for explaining a second example of a method of setting an important monitoring area. (A) and (B) are schematic diagrams for explaining a third example of a method of setting an important monitoring area. FIG. 4 is a schematic diagram for explaining a search using a parameter-free genetic algorithm; FIG. 4 is a perspective view for explaining a plurality of straight lines extending from the imaging device; FIG. 4 is a schematic diagram for explaining the relationship between an imaging range and a plurality of straight lines; FIG. 4 is a perspective view for explaining a plurality of straight lines extending from a plurality of imaging devices in a monitoring area; FIG. 4 is a schematic diagram for explaining the effective range of a straight line extending from the imaging device; It is a block diagram which shows the structure of a computer roughly. 4 is a flowchart showing processing of the information processing apparatus according to Embodiment 1; FIG. 4 is a perspective view showing an example of superimposing duplicate voxels on standard voxels; 9 is a flowchart showing processing of an information processing apparatus according to Embodiment 2; FIG. 12 is a block diagram schematically showing the configuration of an information processing apparatus according to Embodiments 3 and 4; It is a schematic diagram showing an example of a score setting screen. 8A and 8B are perspective views for explaining a counting method when a straight line extending from an imaging device contacts a point-assigned voxel; FIG. 10 is a flowchart showing processing of an information processing apparatus according to Embodiment 3; (A) and (B) are perspective views showing an example of point-allotted voxels included in an important monitoring area and an example of overlapping voxels arranged to overlap the point-allotted voxels. 10 is a flowchart showing processing of an information processing device according to Embodiment 4; 14 is a flow chart showing processing of an information processing apparatus according to Embodiment 5. FIG.

Embodiment 1.
FIG. 1 is a block diagram schematically showing the configuration of an information processing apparatus 100 according to Embodiment 1. As shown in FIG.
Information processing apparatus 100 includes storage unit 110 , display unit 120 , input unit 130 , and control unit 140 .

The storage unit 110 stores information and programs necessary for processing in the information processing apparatus 100 . For example, the storage unit 110 stores monitoring area information and imaging device information.
The monitored area information indicates a virtual monitored area. For example, the monitoring area information indicates the shape and size of the monitoring area. Furthermore, the monitored area information may include information indicating the position, shape and size of obstacles placed within the monitored area.

FIG. 2 is a perspective view showing an example of a monitoring area indicated by monitoring area information.
In Embodiment 1, the monitoring area is a rectangular parallelepiped room 150 with a width of 20 m (meters), a depth of 20 m, and a height of 3 m.
Here, in Embodiment 1, the monitoring area is indicated by coordinates with the point P as the origin, the width direction of the monitoring area as the x axis, the depth direction as the y axis, and the height direction as the z axis. shall be
In the first embodiment, rectangular parallelepiped pillars 151A, 151B, and 151C having a width of 1 m, a depth of 1 m, and a height of 3 m are arranged at predetermined positions in the above-described coordinates in the room 150. shall be

The imaging device information indicates the performance of each of the plurality of imaging devices arranged in the monitoring area. The imaging device is a video camera capable of capturing moving images, and is used as a surveillance camera. For example, the imaging device information indicates at least the angle of view and image quality of the imaging device. In Embodiment 1, the image quality is the screen resolution, but it may be the number of pixels. The number of pixels here may be the number of effective pixels or the total number of pixels. In addition to a video camera, an infrared camera may be used as the imaging device.

Returning to FIG. 1, the display unit 120 displays various screen images.
Input unit 130 receives an instruction input from the user.

The control unit 140 controls processing in the information processing device 100 .
The control unit 140 includes a monitoring area setting unit 141 , an important monitoring area setting unit 142 and an optimum placement search unit 143 .

The monitoring area setting unit 141 reads the monitoring area information stored in the storage unit 110 and sets the monitoring area indicated by the read monitoring area information as the search target monitoring area.
Then, the monitoring area setting unit 141 fills the monitoring area with voxels by arranging a plurality of voxels in the monitoring area indicated by the monitoring area information so that the voxels do not overlap each other. Here, voxels are objects to be counted. The voxels arranged by the monitoring region setting unit 141 are hereinafter referred to as standard voxels or first voxels. A standard voxel has a predetermined shape and size, and is a rectangular parallelepiped with a width of 1 m, a depth of 1 m, and a height of 0.5 m in the first embodiment.
For example, the monitored area, room 150, shown in FIG. 2 would be filled with 2400 voxels.

The focused monitoring area setting unit 142 sets a focused monitoring area, which is an area to be monitored intensively, in the monitoring area indicated by the monitoring area information. For example, the important monitoring area setting unit 142 causes the display unit 120 to display an important monitoring area input screen image indicating the monitoring area, and receives an input of the important monitoring area from the user via the input unit 130 .

FIGS. 3(A) and (B), FIGS. 4(A) and (B), and FIGS. 5(A) and (B) are schematic diagrams for explaining a method of setting an important monitoring area.
First, FIG. 3A shows a part of the focused monitoring area input screen image displayed on the display unit 120 .
As shown in FIG. 3A, the key monitoring area input screen image shows a plan view of the monitoring area indicated by the monitoring area information, viewed from above. A number of standard voxels placed in the monitored area by unit 141 are also shown.

The user uses the input unit 130 to input the important monitoring area R1 on the important monitoring area input screen image, as shown in FIG. 3A.
Upon receiving the input of the important monitoring region R1, the important monitoring region setting unit 142 divides the standard voxels included in the inputted important monitoring region R1 as shown in FIG. , to generate segmented voxels. A split voxel is a voxel of smaller size than a standard voxel. Here, the divided voxels are assumed to be half the size of the standard voxels, but the embodiment is not limited to such an example. For example, the divided voxels may be one-third the size of the standard voxels by vertically and horizontally dividing the standard voxels into thirds, or may have a different shape from the standard voxels.
Note that the user can input one or more focused monitoring areas into the monitoring area.

Furthermore, as shown in FIG. 4A, the user can further input an important monitoring area R2 within the range designated as the important monitoring area.
Even in such a case, upon receiving the input of the important monitoring region R2, the important monitoring region setting unit 142 determines that it is included in the inputted important monitoring region R2 as shown in FIG. 4(B). Divided voxels are generated by further dividing the divided voxels. It is assumed that the divided voxels divided here have half the size of the original divided voxels.

Further, as shown in FIG. 5(A), the user further inputs the important monitoring area R3 within the range designated as the important monitoring area, thereby obtaining can be made to generate further subdivided voxels.

As described above, the focused monitoring area setting unit 142 generates a plurality of divided voxels by dividing each standard voxel in the focused monitoring area. Here, the divided voxels are also referred to as second voxels.

Returning to FIG. 1, the optimum placement search unit 143 searches for efficient positions and orientations when monitoring a monitoring area with a plurality of imaging devices. Here, it is assumed that the number of the plurality of imaging devices arranged in the monitoring area is determined in advance by input from the user or the like.

For example, the optimum placement search unit 143 changes at least one of the positions and orientations of at least some of the plurality of imaging devices virtually arranged in the monitoring area, and obtains the plurality of imaging ranges of the plurality of imaging devices. By repeating the process of calculating the score by counting the values obtained from the space in which a plurality of standard voxels included in any of are arranged, the arrangement that maximizes the score under predetermined conditions is searched for. do. Here, the optimum placement search unit 143 makes the value obtained from the space in which the standard voxels are placed within the important monitoring area higher than the value obtained from the space in which the standard voxels are placed outside the important monitoring area. to calculate the score.

Specifically, the optimum placement search unit 143 virtually places a plurality of imaging devices in random orientations and positions in the monitoring area. Then, the optimum arrangement search unit 143 counts the number of standard voxels and divided voxels included in the imaging range of any one of the plurality of imaging devices, and arranges the plurality of voxels so that the score indicated by the count value becomes maximum. searching for the optimum arrangement while changing at least one of the position and orientation of at least one of the imaging devices.

A known search method such as meta-heuristic may be used as a method for searching for the optimum arrangement of the plurality of imaging devices. In Embodiment 1, optimal placement search section 143 searches using a genetic algorithm, and more specifically, searches using a parameter-free genetic algorithm (hereinafter referred to as PfGA). there is

FIG. 6 is a schematic diagram showing an example of genetic information used in PfGA.
In FIG. 6, the positions of n (n is an integer equal to or greater than 1) imaging devices are represented by three axes of "Position X", "Position Y" and "Position Z", and the orientation of the imaging device is "Angle X", "Angle Y" and "Angle Z" are represented by rotation angles about three axes.

In Embodiment 1, the optimal placement search unit 143 counts the number of divided voxels included in any of the plurality of imaging ranges of the plurality of imaging devices within the focused monitoring area, and counts the number of divided voxels outside the focused monitoring area. , the score is calculated by counting the number of standard voxels included in any one of a plurality of imaging ranges.

Next, the determination of whether or not there are standard voxels or divided voxels within the imaging range of the imaging device will be described. In the following description, standard voxels or divided voxels are simply referred to as voxels.

The optimum arrangement search unit 143 identifies the imaging range of the imaging device from the angle of view of the imaging device indicated by the imaging device information stored in the storage unit 110 .
Then, as shown in FIG. 7, the optimal placement search unit 143 locates one point 162 of the imaging device 160, for example, the intersection of the outer surface of the lens 161 and the optical axis, within the specified imaging range. , a plurality of straight lines 163 are virtually generated radially. A plurality of straight lines 163 are radially generated so as to fill the imaging range so that the straight lines 163 do not intersect at points other than the point 162 .

FIG. 8 shows an example of a method of generating a plurality of straight lines by the optimum placement searching section 143. In FIG.
In FIG. 8, a rectangle 164 indicates an imaging range on a plane that is a predetermined distance away from the imaging device and perpendicular to its optical axis. A plurality of points within the rectangle 164 are points of intersection between the plane and a plurality of straight lines generated by the optimum placement search section 143 .

As shown in FIG. 8, the optimum layout search unit 143 may generate a plurality of straight lines so that the straight lines are evenly distributed within a rectangle 164 representing the imaging range.
Specifically, the optimal layout search unit 143 identifies the number of vertical and horizontal pixels from the screen resolution of the imaging device indicated by the imaging device information stored in the storage unit 110 . The optimum layout search unit 143 may generate a plurality of straight lines so that the number of intersections in vertical columns and the number of intersections in horizontal columns in the imaging range are proportional to the specified number of pixels.

Here, the number of the plurality of straight lines generated by the optimum layout search unit 143 can be increased as the image quality of the imaging device indicated by the imaging device information is higher. Here, it is possible to increase the number of straight lines as the screen resolution increases. As a result, the number of straight lines can indicate the performance of the imaging device.

Then, as shown in FIG. 9, the optimum placement searching unit 143 arranges the imaging devices 160A to 160E in the room 150, which is the monitoring area, and calculates voxels where a plurality of straight lines extending from the imaging devices 160A to 160E come into contact. count the number of Here, even if a plurality of straight lines come into contact, the value counted from one voxel is "1", and the voxels counted by any one of the plurality of imaging devices 160A to 160E are counted by the remaining imaging devices. Devices 160A-160E do not count.

For example, as indicated by the straight line extending from the imaging device 160C, when the straight line contacts an obstacle such as the pillar 151B, the straight line stops at the contact portion.
Although five imaging devices 160A to 160E are arranged in FIG. 9, the number of imaging devices 160 is not limited to five, and may be one or more.

Further, for example, there are cases where it is desired to capture an image within a predetermined size range within an image captured by an imaging device, such as a person's face. In such a case, the straight line generated by the optimum layout search unit 143 may be provided with an effective range according to the performance of the imaging device.
As shown in FIG. 10, by predetermining an effective range 165 in which an object can be imaged within a predetermined size range on a straight line 163A extending from a point 162 of the imaging device 160, the optimum The placement search unit 143 counts the voxels when they come into contact with this effective range 165 , and does not count those voxels when they come into contact outside this effective range 165 .

Information indicating such an effective range may be included in the imaging device information in the storage unit 110, or may be input by the user via the input unit 130 before searching.

The information processing apparatus 100 described above includes, for example, a CPU (Central Processing Unit) 11, a memory 12, and a storage device 13 such as a HDD (Hard Disk Drive) as shown in FIG. , a display 14, and an input device 15 such as a keyboard and mouse.
For example, the storage unit 110 can be implemented by the CPU 11 using the memory 12 or the storage device 13, and the control unit 140 causes the CPU 11 to load a program stored in the storage device 13 into the memory 12 and It can be realized by executing a program, the display unit 120 can be realized by the CPU 11 using the display 14 , and the input unit 130 can be realized by the CPU 11 using the input device 15 .

Such a program may be provided through a network, or recorded on a recording medium and provided. That is, such programs may be provided as program products, for example.

FIG. 12 is a flow chart showing processing of the information processing apparatus 100 according to the first embodiment.
First, the monitoring area setting unit 141 reads the monitoring area information stored in the storage unit 110, and sets the monitoring area indicated by the read monitoring area information as the search target monitoring area (S10).

Next, the monitoring region setting unit 141 fills the monitoring region with standard voxels by arranging a plurality of standard voxels in the set monitoring region so that they do not overlap each other (S11).

Next, the important monitoring area setting unit 142 sets an important monitoring area, which is an area to be monitored intensively, in the set monitoring area (S12). For example, the important monitoring area setting unit 142 displays an important monitoring area input screen image and receives an input of the important monitoring area from the user via the input unit 130 .

Next, the focused monitoring region setting unit 142 generates divided voxels by dividing the standard voxels included in the set focused monitoring region (S13).

Next, the important monitoring area setting unit 142 determines whether or not the setting of the important monitoring area is completed (S14). For example, when the user uses the input unit 130 to input an instruction to end the setting of the important monitoring area in the important monitoring area input screen image displayed on the display unit 120, the important monitoring area setting unit 142 It is sufficient to determine that the setting of the monitoring area is completed. Then, if the setting of the important monitoring area has been completed (Yes in S14), the process proceeds to step S15, and if the setting of the important monitoring area has not been completed (No in S14), the process proceeds to step S12. return.

In step S15, the optimum arrangement search unit 143 arranges a plurality of imaging devices at random positions and orientations in the set monitoring area (S15).

Next, the optimal placement search unit 143 counts the number of standard voxels and divided voxels that touch a straight line extending from any one of the plurality of imaging devices placed in the monitoring area, and uses the counted value as a score. Calculate (S16).

Next, the optimum placement search unit 143 determines whether or not the score calculated in step S16 is the maximum value (S17). If the score is the maximum value (Yes at S17), the process proceeds to step S18, and if the score is not the maximum value (No at S17), the process proceeds to step S19.

In step S18, the optimum placement search unit 143 stores in the storage unit 110 the optimum placement information indicating the placement for which the maximum score is calculated. Optimal arrangement information is information indicating the positions and orientations of a plurality of imaging devices. Note that the optimal placement search unit 143 sets the initial value of the maximum value to “0” to store the positions and orientations of the plurality of imaging devices in the initial placement in the storage unit 110 as optimal placement information. Then, the process proceeds to step S19.

In step S19, the optimum placement search unit 143 determines whether or not the score is saturated. For example, when the generation in the genetic algorithm reaches a predetermined generation, when the maximum value of the score is equal to or greater than a predetermined threshold value, or when the score calculated in step S16 and the previously calculated score When the number of times the difference from the score is equal to or less than a predetermined threshold is equal to or greater than the predetermined threshold, the optimum placement search unit 143 may determine that the score has been saturated. If the score is saturated (Yes in S19), the process ends, and if the score is not saturated (No in S19), the process proceeds to step S20.

In step S20, the optimum placement search unit 143 changes the positions and orientations of the plurality of imaging devices according to the PfGA. Then, the process returns to step S16.

As described above, according to Embodiment 1, by reducing the size of the voxels arranged in the area to be monitored intensively, the score calculated when this area is included in the imaging range is relatively low. become significantly larger. Therefore, it is possible to efficiently arrange a plurality of imaging devices so that an area to be monitored intensively is monitored.

Embodiment 2.
As shown in FIG. 1 , information processing apparatus 200 according to the second embodiment includes storage section 110 , display section 120 , input section 130 and control section 240 .
Storage unit 110, display unit 120, and input unit 130 in the second embodiment are the same as storage unit 110, display unit 120, and input unit 130 in the first embodiment.

The control unit 240 according to the second embodiment controls processing in the information processing device 200 .
The control unit 240 includes a monitoring area setting unit 141 , an important monitoring area setting unit 242 and an optimum placement search unit 243 .
The monitoring area setting unit 141 according to the second embodiment is the same as the monitoring area setting unit 141 according to the first embodiment.

The focused monitoring area setting unit 242 sets a focused monitoring area, which is an area to be monitored intensively, in the monitoring area indicated by the monitoring area information.
When an important monitoring area is set within the monitoring area, the important monitoring area setting unit 142 according to the first embodiment generates divided voxels by subdividing the standard voxels in the important monitoring area. On the other hand, when the important monitoring area setting unit 242 in the second embodiment sets the important monitoring area within the monitoring area, as shown in FIG. Voxel 270 is superimposed by placing it at the same position as standard voxel 271 in the focused monitoring area. Note that the overlapping voxels are also referred to as second voxels.

The optimum placement search unit 243 counts the number of standard voxels and overlapping voxels included in any of the plurality of imaging ranges of the plurality of imaging devices within the priority monitoring area, and counts the number of the plurality of imaging voxels outside the priority monitoring area. A score is calculated by counting the number of standard voxels that fall within any of the ranges.

As a result, when searching for the optimal placement of a plurality of imaging devices, the optimal placement search unit 243 can include the number of overlapping voxels in addition to the standard voxels in the score if the focused monitoring area is included in the imaging range. Therefore, the score in that case can be made relatively large.

In the second embodiment as well, the value counted from one voxel is "1", and the voxels counted by any one of the plurality of imaging devices 160A to 160E are counted by the remaining imaging devices 160A to 160E. Then it won't count. However, in the second embodiment, since a plurality of counts are performed from the space in which the standard voxels and overlapping voxels are arranged, the arrangement in which the focused monitoring area is included in the imaging range is given priority. .

Although FIG. 13 shows an example in which one overlapping voxel 270 is superimposed on the standard voxel 271, a plurality of overlapping voxels may be superimposed on one standard voxel.

FIG. 14 is a flow chart showing processing of the information processing apparatus 200 according to the second embodiment.
In the flowchart shown in FIG. 14, the same reference numerals as in FIG. 12 denote steps that perform the same processing as in the flowchart of the first embodiment shown in FIG. 12, and detailed description thereof will be omitted.

The processing of steps S10 to S12 in FIG. 14 is the same as the processing of steps S10 to S12 in FIG. However, in FIG. 14, the process proceeds to step S33 after the process of step S12.

In step S33, the focused monitoring area setting unit 242 arranges overlapping voxels so as to overlap the standard voxels included in the set focused monitoring area. Then, the process proceeds to step S14.

The processing of steps S14 and S15 in FIG. 14 is the same as the processing of steps S14 and S15 in FIG. However, in FIG. 14, the process proceeds to step S36 after the process of step S15.

In step S36, the optimal placement search unit 243 counts the number of standard voxels and overlapping voxels that touch a straight line extending from any one of the plurality of imaging devices placed in the monitoring area, and scores the counted value. Calculate as Then, the process proceeds to step S17.

The processing of steps S17-S20 in FIG. 14 is the same as the processing of steps S17-S20 in FIG. However, in FIG. 14, the process returns to step S36 after the process of step S20.

As described above, according to Embodiment 2, by arranging overlapping voxels in a region to be monitored intensively, voxels arranged at the same location can be counted by a plurality of imaging devices. It becomes possible to monitor the same area intensively with the device of .

Embodiment 3.
FIG. 15 is a block diagram schematically showing the configuration of information processing apparatus 300 according to the third embodiment.
The information processing device 300 includes a storage unit 110 , a display unit 120 , an input unit 130 and a control unit 340 .
Storage unit 110, display unit 120, and input unit 130 in the third embodiment are the same as storage unit 110, display unit 120, and input unit 130 in the first embodiment.

The control unit 240 according to Embodiment 3 controls processing in the information processing device 300 .
The control unit 340 includes a monitoring area setting unit 141 , an important monitoring area setting unit 342 , an optimal placement search unit 343 and a point allocation setting unit 344 .
The monitoring area setting unit 141 according to the third embodiment is the same as the monitoring area setting unit 141 according to the first embodiment.

The focused monitoring area setting unit 342 sets a focused monitoring area, which is an area to be monitored intensively, in the monitoring area indicated by the monitoring area information.
For example, the important monitoring area setting unit 342 causes the display unit 120 to display an important monitoring area input screen image indicating the monitoring area, and receives an input of the important monitoring area from the user via the input unit 130 .

The point allocation setting unit 344 generates point allocation voxels by setting scores for each of a plurality of surfaces of standard voxels included in the important monitoring area set by the important monitoring area setting unit 342 . Since the standard voxel is a rectangular parallelepiped, points are set here for six faces. Here, the scored voxel is a voxel in which a score is set for each surface of the standard voxel, and is also referred to as a second voxel.

For example, the point allocation setting unit 344 causes the display unit 120 to display a point allocation setting screen showing the voxels 372 as shown in FIG. 372c can be received. Note that when the score input for all the surfaces 372a to 372c of the voxel 372 shown in FIG. , the input of the scores of the remaining faces may be accepted.

Note that the point allotment setting unit 344 may receive an input of the score of each surface for all the standard voxels included in the set focused monitoring area, and the score received for one standard voxel is May be assigned to standard voxels.

Returning to FIG. 15, the optimal placement search unit 343 searches for efficient positions and orientations when monitoring a monitoring area with a plurality of imaging devices. Here, it is assumed that the number of the plurality of imaging devices arranged in the monitoring area is determined in advance by input from the user or the like.
Here, in Embodiment 3, the optimum placement search unit 343 uses a method of obtaining values from the space in which the standard voxels are arranged within the focused monitoring area, and a method of obtaining values from the space in which the standard voxels are placed outside the focused monitoring area. Change how you get.
For example, in Embodiment 3, the optimum placement search unit 343, in the focused monitoring area, sets a value corresponding to the score set to the scored voxel included in one of the plurality of imaging ranges of the plurality of imaging devices. is counted, and the number of standard voxels included in any one of a plurality of imaging ranges is counted outside the focused monitoring area to calculate the score.
In other words, the optimal placement search unit 343 uses a method of obtaining a value from the space in which the standard voxels are placed in the focused monitoring area as a method of obtaining a value from the allocated voxel that is included in one of the plurality of imaging ranges of the plurality of imaging devices. Count the value according to the score obtained. Then, the optimum placement search unit 343 counts the number of standard voxels included in any one of the plurality of imaging ranges as a method of obtaining a value from the space in which the standard voxels are placed outside the focused monitoring area.

Specifically, the optimum arrangement search unit 343 arranges a plurality of imaging devices in random orientations and positions in the monitoring area. Then, the optimum placement search unit 143 counts the number of standard voxels included in the imaging range of any one of the plurality of imaging devices and the score obtained from the allocated voxels, and the score indicated by the count value is the maximum. The optimum arrangement is searched for while changing the position and orientation of at least one of the plurality of imaging devices so that .

The counting by the optimum placement searching unit 343 in the third embodiment is the same as in the first embodiment when the straight line extending from the imaging device touches the standard voxel.
A method of counting when a straight line extending from an imaging device contacts a point-allocated voxel will be described below.

FIGS. 17A and 17B are perspective views for explaining a counting method when a straight line extending from an imaging device contacts a point-allocated voxel.
17A and 17B show an example of the arrangement of the plurality of imaging devices 360A and 360B by the optimum arrangement search unit 343, and the point allocation voxel 373 is included in the imaging range of the plurality of imaging devices 360A and 360B. ing.

As shown in FIG. 17A, the score "3" is assigned to the surface 373a of the scored voxel 373, the score "3" is assigned to the surface 373b, and the score "1" is assigned to the surface 373c. do.
As shown in FIG. 17A, when a plurality of straight lines extending from the imaging device 360A touch three surfaces 373a, 373b, and 373c of the point-allocated voxel 373, the optimum placement search section 343 determines that the plurality of straight lines The maximum score "3" assigned to the three contacting surfaces 373a, 373b, and 373c is counted from the assigned voxel 373 for the imaging device 360A.

On the other hand, as shown in FIG. 17B, the score "4" is assigned to the surface 373d, and a plurality of straight lines extending from the imaging device 160B are projected onto the three surfaces 373a, 373b, and 373d of the scored voxel 373. In the case of contact, the optimal placement search unit 343 assigns the maximum score "4" to the three surfaces 373a, 373b, and 373d with which the plurality of straight lines contact, to the imaging device 360B. It counts from the scored voxel 373 .

Then, the optimal placement search unit 343, in the placement of the plurality of imaging devices 360A and 360B shown in FIG. A score of "4", which is the larger one of the score "4" counted in 360B, is adopted to count the score in that arrangement.
However, the contact between the surfaces 373a to 373d of the point-allocation voxel 373 and the plurality of straight lines is limited only to the case of contact from the outside of the point-allocation voxel 373. FIG. In other words, when the straight line touches the surfaces 373a to 373d after passing through the point allocation voxel 373, the optimal placement search section 343 does not count.

As described above, the optimal placement search unit 343 is arranged to face any one of the plurality of imaging devices among the plurality of planes of the point-allocated voxels included in any of the plurality of imaging ranges of the plurality of imaging devices. Count the highest score among the points set for the surface to be touched.

FIG. 18 is a flow chart showing processing of the information processing apparatus 300 according to the third embodiment.
In the flowchart shown in FIG. 18, the same reference numerals as in FIG. 12 denote steps that perform the same processing as in the flowchart of the first embodiment shown in FIG. 12, and detailed description thereof will be omitted.

The processing of steps S10 to S12 in FIG. 18 is the same as the processing of steps S10 to S12 in FIG. However, in FIG. 18, the process proceeds to step S43 after the process of step S12.

In step S43, the point allotment setting unit 344 sets points for the planes forming the standard voxels included in the set important monitoring region. Then, the process proceeds to step S14.

The processing of steps S14 and S15 in FIG. 18 is the same as the processing of steps S14 and S15 in FIG. However, in FIG. 18, the process proceeds to step S46 after the process of step S15.

In step S46, the optimal placement search unit 343 determines the number of standard voxels that are in contact with a straight line extending from any one of the plurality of imaging devices placed in the monitoring area, and By counting the number of points obtained from allotted voxels in contact with a straight line extending from , the counted value is calculated as a score. Then, the process proceeds to step S17.

The processing of steps S17-S20 in FIG. 18 is the same as the processing of steps S17-S20 in FIG. However, in FIG. 18, the process returns to step S46 after the process of step S20.

As described above, according to the third embodiment, it is possible to assign points to voxel planes in a region to be monitored intensively. It can be reflected in the arrangement of the equipment.
For example, when monitoring a person who enters a room through a door, the area near the door is set as an important monitoring area, and a high score is set for the voxel of the important monitoring area on the surface on the indoor side, so that such a person can be monitored. A suitable arrangement of multiple imaging devices for monitoring can be obtained.

In the third embodiment described above, the optimum placement search unit 343 selects the most points among the plurality of surfaces of the point-allocated voxels set on the surface facing any one of the plurality of imaging devices. Although high scores are counted, Embodiment 3 is not limited to such an example. For example, the optimum placement search unit 343 determines the number of points set on the plane facing each of the plurality of imaging devices among the plurality of planes of each point-allocated voxel included in one of the plurality of imaging ranges. The highest sum of sums may be counted.

Embodiment 4.
As shown in FIG. 15 , information processing apparatus 400 according to the fourth embodiment includes storage section 110 , display section 120 , input section 130 and control section 440 .
Storage unit 110, display unit 120 and input unit 130 in the fourth embodiment are the same as storage unit 110, display unit 120 and input unit 130 in the first embodiment.

The control unit 440 according to the fourth embodiment controls processing in the information processing device 400 .
The control unit 440 includes a monitoring area setting unit 141 , an important monitoring area setting unit 442 , an optimal placement search unit 443 and a score setting unit 444 .
The monitoring area setting unit 141 according to the fourth embodiment is the same as the monitoring area setting unit 141 according to the first embodiment.

The focused monitoring area setting unit 442 sets a focused monitoring area, which is an area to be monitored intensively, in the monitoring area indicated by the monitoring area information.
For example, the important monitoring area setting unit 442 causes the display unit 120 to display an important monitoring area input screen image indicating the monitoring area, and receives an input of the important monitoring area from the user via the input unit 130 .

Then, when the important monitoring area is set within the monitoring area, the important monitoring area setting unit 442 creates overlapping voxels having the same shape and size as the standard voxels, similarly to the important monitoring area setting unit 242 of the second embodiment. They are superimposed by arranging them at the same positions as the standard voxels in the focus monitoring area.

As in the third embodiment, the score setting unit 444 sets a score for each of a plurality of planes (here, six planes) of the standard voxels included in the set focused monitoring region, Generate scored voxels. Here, the point-allocated voxels in Embodiment 4 are also referred to as second voxels.
Also, the allotment setting unit 444 sets a score for each of a plurality of planes (here, six planes) of overlapping voxels arranged by the important monitoring region setting unit 442 . Here, the overlapping voxels in Embodiment 4 are also referred to as third voxels. Note that the method for setting the score on the surface of the overlap voxel may be the same as the method for setting the score on the surface of the standard voxel.

FIGS. 19A and 19B are perspective views showing an example of point-allocated voxels included in the focused monitoring area and an example of overlapping voxels arranged overlapping the point-allocated voxels.
As shown in FIG. 19A, in the scored voxel 474, the surface 474a and the surface 474b are assigned a score of "0", and the surface 474c is assigned a score of "3".
On the other hand, as shown in FIG. 19B, in the overlap voxel 475 that overlaps the scored voxel 474, the score "0" is set for the surface 475a and the surface 475b, and the score "3" is set for the surface 475d. ” is set.

As shown in FIG. 19A, in the scored voxel 474, a high score is set for the surface 474c. score higher.

On the other hand, as shown in FIG. 19B, in the overlapping voxel 475, a high score is set for the surface 475d. the higher the score.

Therefore, by superimposing the overlapping voxels 475 on the scored voxels 474, a high score can be obtained when an imaging device is arranged to take an image from the direction D1 and another imaging device is arranged to take an image from the direction D2. can be made to be
Therefore, the fourth embodiment is effective when it is desired to monitor the important monitoring area from multiple directions.

The optimal placement search unit 443 searches for efficient positions and orientations when monitoring a monitoring area with a plurality of imaging devices. Here, it is assumed that the number of the plurality of imaging devices arranged in the monitoring area is determined in advance by input from the user or the like.
Here, in the fourth embodiment as well, the optimum placement search unit 443 uses a method of obtaining values from the space in which the standard voxels are arranged within the important monitoring area and a method of obtaining values from the space in which the standard voxels are arranged outside the important monitoring area. Change how you get.
For example, the optimum placement search unit 443 determines, within the focused monitoring area, a value corresponding to the number of points set for a point-allocated voxel included in any of the imaging ranges of the plurality of imaging devices and any of the plurality of imaging ranges. The score is calculated by counting the value corresponding to the score set for the overlapping voxels included, and counting the number of standard voxels included in any of the multiple imaging ranges outside the focused monitoring area. do.
In other words, the optimum placement search unit 443 uses a method of obtaining a value from the space in which the standard voxels are placed in the focused monitoring area, and sets the point allocation voxel included in one of the plurality of imaging ranges of the plurality of imaging devices. A value corresponding to the number of points obtained and a value corresponding to the number of points set for overlapping voxels included in any of the plurality of imaging ranges are counted. Then, the optimum placement search unit 443 counts the number of standard voxels included in any one of a plurality of imaging ranges as a method of obtaining a value from the space in which the standard voxels are placed outside the focused monitoring area.

Specifically, the optimum arrangement search unit 443 arranges a plurality of imaging devices in random orientations and positions in the monitoring area. Then, the optimum placement search unit 143 counts the number of standard voxels included in the imaging range of any one of the plurality of imaging devices, and the points obtained from the scored voxels and overlapping voxels, and the count value indicates The optimum arrangement is searched for while changing at least one of the position and orientation of at least one of the plurality of imaging devices so as to maximize the score.

The counting of points obtained from allocated voxels and overlapping voxels in the fourth embodiment is the same as the counting of points obtained from allocated voxels in the third embodiment.
For example, the optimal placement search unit 443 determines the number of points set on the surface facing any one of the plurality of imaging devices among the plurality of surfaces of each point-allocated voxel included in any of the plurality of imaging ranges. count the highest score among In addition, the optimum placement search unit 443 determines the number of points set on the surface facing any one of the plurality of imaging devices, among the plurality of surfaces of each of the overlapping voxels included in any of the plurality of imaging ranges. count the highest score among

Also in Embodiment 4, the optimum placement search unit 443 selects the plane facing each of the plurality of imaging devices among the plurality of planes of each point-allocated voxel included in one of the plurality of imaging ranges. count the highest total value among the total values of the points set in the plurality of imaging devices among the plurality of planes of each overlapping voxel included in one of the plurality of imaging ranges. The highest total value among the total values of points set on the surfaces facing each other may be counted.

FIG. 20 is a flow chart showing processing of the information processing apparatus 400 according to the fourth embodiment.
In the flowchart shown in FIG. 20, the same reference numerals as in FIG. 12 denote steps that perform the same processing as in the flowchart of the first embodiment shown in FIG. 12, and detailed description thereof will be omitted.

The processing of steps S10 to S12 in FIG. 20 is the same as the processing of steps S10 to S12 in FIG. However, in FIG. 20, the process proceeds to step S53-1 after the process of step S12.

In step S53-1, the focused monitoring area setting unit 442 arranges overlapping voxels so as to overlap the standard voxels included in the set focused monitoring area. Then, the process proceeds to step S53-2.

In step S53-2, the point allocation setting unit 444 sets points for the planes forming the standard voxels and overlapping voxels included in the set important monitoring area. Then, the process proceeds to step S14.

The processes of steps S14 and S15 in FIG. 20 are the same as the processes of steps S14 and S15 in FIG. However, in FIG. 20, the process proceeds to step S56 after the process of step S15.

In step S56, the optimal placement search unit 443 determines the number of standard voxels that are in contact with a straight line extending from any one of the plurality of imaging devices placed in the monitoring area, and By counting the points obtained from allotted voxels and overlapping voxels touching a straight line extending from , the counted value is calculated as a score. Then, the process proceeds to step S17.

The processing of steps S17-S20 in FIG. 20 is the same as the processing of steps S17-S20 in FIG. However, in FIG. 20, the process returns to step S56 after the process of step S20.

As described above, according to Embodiment 4, voxels can be arranged so as to overlap the voxels of the region to be monitored intensively, and points can be assigned to the planes of those voxels. A plurality of directions desired to be monitored at locations where voxels are arranged can be reflected in the arrangement of a plurality of imaging devices. Thereby, it is possible to arrange a plurality of imaging devices so as to monitor from a plurality of directions desired to be monitored from a plurality of directions.
For example, when monitoring a person entering or exiting a room through a door, the vicinity of the door is set as an important monitoring area. By setting a high score to , it is possible to obtain a suitable arrangement of a plurality of imaging devices for monitoring such an area from a plurality of directions.

Embodiment 5.
As shown in FIG. 1 , information processing apparatus 500 according to Embodiment 5 includes storage section 110 , display section 120 , input section 130 and control section 540 .
Storage unit 110, display unit 120 and input unit 130 in the fifth embodiment are the same as storage unit 110, display unit 120 and input unit 130 in the first embodiment.

The control unit 540 in Embodiment 5 controls processing in the information processing device 500 .
The control unit 540 includes a monitoring area setting unit 141 , an important monitoring area setting unit 542 and an optimal placement search unit 543 .
The monitoring area setting unit 141 according to the fifth embodiment is the same as the monitoring area setting unit 141 according to the first embodiment.

The focused monitoring area setting unit 542 sets the focused monitoring area, which is the area to be monitored intensively, in the monitoring area indicated by the monitoring area information, as in the first embodiment.
Next, the priority monitoring area setting unit 542 sets a high-priority monitoring area, which is an area to be monitored more intensively, within the priority monitoring area according to an instruction from the user.
Then, when the high-priority monitoring region is set, the high-priority monitoring region setting unit 542 arranges overlapping voxels, which are voxels having the same shape and size as the divided voxels, at the same positions as the divided voxels in the high-weighted monitoring region. By doing so, they overlap. The setting of the high-priority monitoring area may be performed within the high-priority monitoring area in the same procedure as the setting of the high-priority monitoring area described in the first embodiment. Here, the divided voxels in the fifth embodiment are also referred to as second voxels, and the overlapping voxels in the fifth embodiment are also referred to as third voxels.

The optimum placement search unit 543 counts the number of divided voxels and overlapping voxels included in any of the plurality of imaging ranges of the plurality of imaging devices within the high-priority monitoring area, and performs the priority monitoring outside the high-priority monitoring area. Within the area, the number of divided voxels included in any of the plurality of imaging ranges of the plurality of imaging devices is counted, and outside the focused monitoring area, the number of standard voxels included in any of the plurality of imaging ranges is counted. Calculate the score by counting the number.

As a result, when searching for the optimal placement of a plurality of imaging devices, the optimal placement search unit 543 can include the number of overlapping voxels in addition to the divided voxels in the score if the high-priority monitoring area is included in the imaging range. Therefore, the score in that case can be made relatively large.

In Embodiment 5 as well, the value counted from one voxel is "1", and the voxels counted by any one of the plurality of imaging devices 160A to 160E are counted by the remaining imaging devices 160A to 160E. Then it won't count. However, in Embodiment 5, since a plurality of counts are performed from the space in which the divided voxels and overlapping voxels are arranged, the arrangement of the plurality of imaging devices in which the focused monitoring area is included in the imaging range is Priority will be given.

FIG. 21 is a flow chart showing processing of the information processing apparatus 500 according to the fifth embodiment.
In the flowchart shown in FIG. 21, the same reference numerals as in FIG. 12 denote steps that perform the same processing as in the flowchart of the first embodiment shown in FIG. 12, and detailed description thereof will be omitted.

The processing of steps S10 to S14 in FIG. 21 is the same as the processing of steps S10 to S14 in FIG. However, in FIG. 21, the process proceeds to step S60 after the process of step S14.

In step S<b>60 , the focused monitoring region setting unit 542 displays an instruction input screen on the display unit 120 to receive an instruction input from the user via the input unit 130 as to whether or not to place overlapping voxels. If overlapping voxels are to be arranged (Yes in S60), the process proceeds to step S61, and if overlapping voxels are not to be arranged (No in S60), the process proceeds to step S15.

In step S61, the important monitoring area setting unit 542 sets a high-important monitoring area, which is an area to be monitored more intensively, within the important monitoring area. For example, as shown in FIG. 5(B), the important monitoring area setting unit 542 displays an important monitoring area input screen image in which the important monitoring area has already been input. Receives the input of the high-priority monitoring area from.

In step S62, the focused monitoring region setting unit 542 arranges overlapping voxels so as to overlap divided voxels included in the set high-weighted monitoring region. Then, the process proceeds to step S63.

In step S63, the priority monitoring area setting unit 542 determines whether setting of the high priority monitoring area has been completed. For example, when the user uses the input unit 130 to input an instruction to end the setting of the high-priority monitoring area in the input screen image of the priority monitoring area displayed on the display unit 120, the priority monitoring area setting unit 542 It is sufficient to determine that the setting of the high-priority monitoring area is completed. Then, if the setting of the high-priority monitoring area has been completed (Yes in S63), the process proceeds to step S15, and if the setting of the high-priority monitoring area has not been completed (No in S63), the process proceeds to step S15. Return to S61.

The process of step S15 in FIG. 21 is the same as the process of step S15 in FIG. However, in FIG. 21, the process proceeds to step S66 after the process of step S15.

In step S66, the optimal placement search unit 543 counts the number of standard voxels, divided voxels, and overlapping voxels that touch a straight line extending from any one of the plurality of imaging devices placed in the monitoring area. Calculate the value as a score. Then, the process proceeds to step S17.

The processing of steps S17-S20 in FIG. 21 is the same as the processing of steps S17-S20 in FIG. However, in FIG. 21, the process returns to step S66 after the process of step S20.

As described above, according to Embodiment 5, by arranging overlapping voxels in a region to be monitored more intensively, voxels arranged at the same location can be counted by a plurality of imaging devices. It becomes possible to focus on monitoring the same area with a plurality of imaging devices.

In the fifth embodiment described above, divided voxels are generated from standard voxels and then overlapping voxels are arranged, but the fifth embodiment is not limited to such an example.
For example, the priority monitoring region setting unit 542 places overlapping voxels (second voxels) in the priority monitoring region, and divides the standard voxels and overlapping voxels included in the high-priority monitoring region to generate divided voxels. You may Here, a divided voxel obtained by dividing a standard voxel is also called a standard divided voxel (third voxel), and a divided voxel obtained by dividing an overlapping voxel is also called an overlapping divided voxel (fourth voxel).
In this case, the optimal placement search unit 543 counts the number of standard voxels, overlapping voxels, standard divided voxels, and overlapping divided voxels that contact a straight line extending from any one of the plurality of imaging devices arranged in the monitoring area. The counted value can be calculated as a score.

In the first to fifth embodiments described above, the optimum arrangement is searched for by changing the position and orientation of the imaging device. , by changing the position, orientation and magnification of the imaging device, the optimal placement may be searched for. In such a case, it is assumed that the imaging device information includes information that can specify the angle of view for each magnification of the imaging device. Specifically, information such as information that associates the magnification with the angle of view, information that associates the range of the magnification with the angle of view, or information indicating a formula for calculating the angle of view from the magnification is stored. It is good if it is.

Reference Signs List 100,200,300,400,500 information processing device 110 storage unit 120 display unit 130 input unit 140,240,340,440,540 control unit 141 monitoring area setting unit 142,242,342,442 , 542 important monitoring area setting unit, 143, 243, 343, 443, 543 optimum arrangement search unit, 344, 444 allotment setting unit.

Claims (34)

a monitoring region setting unit that arranges a plurality of first voxels having a predetermined shape and size in a virtual monitoring region;
an important monitoring area setting unit for setting an important monitoring area, which is an area to be monitored intensively, within the monitoring area;
At least one of the positions and orientations of at least some of the plurality of imaging devices virtually arranged in the monitoring area is changed so that the plurality of imaging devices are included in any one of the plurality of imaging ranges of the plurality of imaging devices. By repeating a process of calculating a score by counting values obtained from a space in which the first voxel is arranged, the score is maximized under a predetermined condition. and an optimal placement search unit that searches for
The focused monitoring area setting unit generates a plurality of second voxels by dividing each first voxel in the focused monitoring area,
The optimal placement search unit counts the number of the second voxels included in any one of the plurality of imaging ranges in the important monitoring area, thereby determining the first voxels in the important monitoring area. calculating the score such that the value obtained from the space in which the voxel is arranged is higher than the value obtained from the space in which the first voxel is arranged outside the focused monitoring area;
An information processing device characterized by: The priority monitoring area setting unit sets a high-priority monitoring area, which is an area to be monitored more intensively, within the priority monitoring area, and in each second voxel within the high-priority monitoring area, superimposing a third voxel of the same shape and size as the shape and size of the second voxel;
The optimal placement search unit calculates the score by counting the number of the second voxels and the third voxels included in any one of the plurality of imaging ranges in the high-priority monitoring area. The information processing apparatus according to claim 1 , characterized by: a monitoring region setting unit that arranges a plurality of first voxels having a predetermined shape and size in a virtual monitoring region;
an important monitoring area setting unit for setting an important monitoring area, which is an area to be monitored intensively, within the monitoring area;
At least one of the positions and orientations of at least some of the plurality of imaging devices virtually arranged in the monitoring area is changed so that the plurality of imaging devices are included in any one of the plurality of imaging ranges of the plurality of imaging devices. By repeating a process of calculating a score by counting values obtained from a space in which the first voxel is arranged, the score is maximized under a predetermined condition. and an optimal placement search unit that searches for
The focused monitoring area setting unit superimposes a second voxel having the same shape and size as the first voxel on each first voxel in the focused monitoring area,
The optimal placement search unit counts the number of the first voxels and the second voxels included in any one of the plurality of imaging ranges in the important monitoring area, thereby determining the important monitoring area. calculating the score such that a value obtained from a space in which the first voxel is arranged within the area is higher than a value obtained from a space in which the first voxel is arranged outside the focused monitoring area. thing
An information processing device characterized by: The priority monitoring area setting unit sets a high-priority monitoring area, which is an area to be monitored more intensively, within the priority monitoring area, and divides each of the first voxels in the high-priority monitoring area. to generate third voxels, and to generate fourth voxels by dividing each of the second voxels in the high-priority monitoring area;
The optimum placement search unit calculates the score by counting the number of the third voxels and the fourth voxels included in any one of the plurality of imaging ranges in the high-priority monitoring area. The information processing apparatus according to claim 3 , characterized in that: a monitoring region setting unit that arranges a plurality of first voxels having a predetermined shape and size in a virtual monitoring region;
an important monitoring area setting unit for setting an important monitoring area, which is an area to be monitored intensively, within the monitoring area;
At least one of the positions and orientations of at least some of the plurality of imaging devices virtually arranged in the monitoring area is changed so that the plurality of imaging devices are included in any one of the plurality of imaging ranges of the plurality of imaging devices. By repeating a process of calculating a score by counting values obtained from a space in which the first voxel is arranged, the score is maximized under a predetermined condition. an optimal placement search unit for searching for
a score setting unit that generates a second voxel by setting a score for each of a plurality of surfaces of each of the first voxels in the focused monitoring area ;
The optimal placement search unit counts a value corresponding to the number of points set for the second voxels included in one of the plurality of imaging ranges within the focused monitoring area, and Then, the score is calculated by counting the number of the first voxels included in any of the plurality of imaging ranges.
An information processing device characterized by: The optimum arrangement search unit is set to a surface facing one of the plurality of imaging devices, among the plurality of surfaces of each of the second voxels included in one of the plurality of imaging ranges. 6. The information processing apparatus according to claim 5 , wherein the highest score among the scores obtained is counted. The optimal placement search unit is set on a surface facing each of the plurality of imaging devices, among the plurality of surfaces of each of the second voxels included in any of the plurality of imaging ranges. 6. The information processing apparatus according to claim 5 , wherein the highest total value among the total values of the points that are obtained is counted. a monitoring region setting unit that arranges a plurality of first voxels having a predetermined shape and size in a virtual monitoring region;
an important monitoring area setting unit for setting an important monitoring area, which is an area to be monitored intensively, within the monitoring area;
At least one of the positions and orientations of at least some of the plurality of imaging devices virtually arranged in the monitoring area is changed so that the plurality of imaging devices are included in any one of the plurality of imaging ranges of the plurality of imaging devices. By repeating a process of calculating a score by counting values obtained from a space in which the first voxel is arranged, the score is maximized under a predetermined condition. an optimal placement search unit for searching for
a score setting unit that generates a second voxel by setting a score for each of a plurality of surfaces of each of the first voxels in the focused monitoring area ;
The important monitoring area setting unit superimposes a third voxel having the same shape and size as the first voxel on each first voxel in the important monitoring area,
The score setting unit sets a score for each of a plurality of surfaces of each third voxel within the focused monitoring area,
The optimal placement search unit is configured to select, within the important monitoring area, a value corresponding to the number of points set for the second voxels included in any one of the plurality of imaging ranges and any one of the plurality of imaging ranges. outside the focused monitoring area, the number of the first voxels included in any one of the plurality of imaging ranges calculating the score by counting
An information processing device characterized by: The optimum arrangement search unit is set to a surface facing one of the plurality of imaging devices, among the plurality of surfaces of each of the second voxels included in one of the plurality of imaging ranges. any one of the plurality of imaging devices among the plurality of planes possessed by each third voxel included in any of the plurality of imaging ranges 9. The information processing apparatus according to claim 8 , wherein the highest score among the scores set on the surface facing the is counted. The optimum arrangement search unit is set to a surface facing one of the plurality of imaging devices, among the plurality of surfaces of each of the second voxels included in one of the plurality of imaging ranges. counting the highest total value among the total values of the points included in the plurality of imaging ranges, and among the plurality of planes possessed by each third voxel included in any of the plurality of imaging ranges, the plurality of planes 9. The information processing apparatus according to claim 8 , wherein the highest total value among the total values of the points set on the surfaces facing each of the imaging devices is counted. The optimum arrangement search unit virtually sets a plurality of straight lines radially extending in a corresponding imaging range of the plurality of imaging ranges from each of the plurality of imaging devices, and the first voxels are arranged in the plurality of 11. The information processing apparatus according to any one of claims 1 to 10 , wherein the first voxel is determined to be in the corresponding imaging range when the first voxel is in contact with any one of the straight lines. The optimum arrangement search unit virtually sets a plurality of straight lines radially extending in a corresponding imaging range of the plurality of imaging ranges from each of the plurality of imaging devices, and the first voxels are arranged in the plurality of When the first voxel is in the corresponding imaging range when it touches any of the straight lines, and when the second voxel touches any of the plurality of straight lines, the second voxel The information processing apparatus according to any one of claims 1 to 7 , wherein the voxels of are in the corresponding imaging range. The optimum arrangement search unit virtually sets a plurality of straight lines radially extending in a corresponding imaging range of the plurality of imaging ranges from each of the plurality of imaging devices, and the first voxels are arranged in the plurality of When the first voxel is in the corresponding imaging range when it touches any of the straight lines, and when the second voxel touches any of the plurality of straight lines, the second voxel is within the corresponding imaging range, and when the third voxel touches any of the plurality of straight lines, determining that the third voxel is within the corresponding imaging range 11. The information processing apparatus according to any one of claims 2 and 8 to 10 , characterized by: The optimum arrangement search unit virtually sets a plurality of straight lines radially extending in a corresponding imaging range of the plurality of imaging ranges from each of the plurality of imaging devices, and the first voxels are arranged in the plurality of When the first voxel is in the corresponding imaging range when it touches any of the straight lines, and when the second voxel touches any of the plurality of straight lines, the second voxel is in the corresponding imaging range, and when the third voxel touches any of the plurality of straight lines, determining that the third voxel is in the corresponding imaging range, 5. The information processing apparatus according to claim 4 , wherein said fourth voxel is determined to be within said corresponding imaging range when said fourth voxel touches any one of said plurality of straight lines. The information processing apparatus according to any one of claims 11 to 14 , wherein the optimum arrangement search unit increases the number of the plurality of straight lines as the image quality of each of the plurality of imaging devices is higher. . The optimum layout search unit determines that the image quality is higher as the screen resolution of each of the plurality of imaging devices is higher or as the number of pixels of each of the plurality of imaging devices is larger. Item 16. The information processing device according to item 15 . 17. The optimum arrangement search unit searches for the arrangement of the plurality of image pickup devices that maximizes the score under a predetermined condition using a genetic algorithm. The information processing device according to item 1. the computer,
a monitoring region setting unit that arranges a plurality of first voxels having a predetermined shape and size in a virtual monitoring region;
an important monitoring area setting unit for setting an important monitoring area, which is an area to be monitored intensively, within the monitoring area;
At least one of the positions and orientations of at least some of the plurality of imaging devices virtually arranged in the monitoring area is changed so that the plurality of imaging devices are included in any one of the plurality of imaging ranges of the plurality of imaging devices. By repeating a process of calculating a score by counting values obtained from a space in which the first voxel is arranged, the score is maximized under a predetermined condition. function as an optimal placement search unit that searches for
The focused monitoring area setting unit generates a plurality of second voxels by dividing each first voxel in the focused monitoring area,
The optimal placement search unit counts the number of the second voxels included in any one of the plurality of imaging ranges in the important monitoring area, thereby determining the first voxels in the important monitoring area. calculating the score such that the value obtained from the space in which the voxel is arranged is higher than the value obtained from the space in which the first voxel is arranged outside the focused monitoring area;
A program characterized by the computer,
a monitoring region setting unit that arranges a plurality of first voxels having a predetermined shape and size in a virtual monitoring region;
an important monitoring area setting unit for setting an important monitoring area, which is an area to be monitored intensively, within the monitoring area;
At least one of the positions and orientations of at least some of the plurality of imaging devices virtually arranged in the monitoring area is changed so that the plurality of imaging devices are included in any one of the plurality of imaging ranges of the plurality of imaging devices. By repeating a process of calculating a score by counting values obtained from a space in which the first voxel is arranged, the score is maximized under a predetermined condition. function as an optimal placement search unit that searches for
The focused monitoring area setting unit superimposes a second voxel having the same shape and size as the first voxel on each first voxel in the focused monitoring area,
The optimal placement search unit counts the number of the first voxels and the second voxels included in any one of the plurality of imaging ranges in the important monitoring area, thereby determining the important monitoring area. calculating the score such that a value obtained from a space in which the first voxel is arranged within the area is higher than a value obtained from a space in which the first voxel is arranged outside the focused monitoring area. thing
A program characterized by the computer,
a monitoring region setting unit that arranges a plurality of first voxels having a predetermined shape and size in a virtual monitoring region;
an important monitoring area setting unit for setting an important monitoring area, which is an area to be monitored intensively, within the monitoring area;
At least one of the positions and orientations of at least some of the plurality of imaging devices virtually arranged in the monitoring area is changed so that the plurality of imaging devices are included in any one of the plurality of imaging ranges of the plurality of imaging devices. By repeating a process of calculating a score by counting values obtained from a space in which the first voxel is arranged, the score is maximized under a predetermined condition. an optimal placement search unit that searches for
Functioning as a score setting unit that generates a second voxel by setting a score for each of a plurality of surfaces of each first voxel in the focused monitoring area ,
The optimal placement search unit counts a value corresponding to the number of points set for the second voxels included in one of the plurality of imaging ranges within the focused monitoring area, and Then, the score is calculated by counting the number of the first voxels included in any of the plurality of imaging ranges.
A program characterized by the computer,
a monitoring region setting unit that arranges a plurality of first voxels having a predetermined shape and size in a virtual monitoring region;
an important monitoring area setting unit for setting an important monitoring area, which is an area to be monitored intensively, within the monitoring area;
At least one of the positions and orientations of at least some of the plurality of imaging devices virtually arranged in the monitoring area is changed so that the plurality of imaging devices are included in any one of the plurality of imaging ranges of the plurality of imaging devices. By repeating a process of calculating a score by counting values obtained from a space in which the first voxel is arranged, the score is maximized under a predetermined condition. an optimal placement search unit that searches for
Functioning as a score setting unit that generates a second voxel by setting a score for each of a plurality of surfaces of each first voxel in the focused monitoring area ,
The important monitoring area setting unit superimposes a third voxel having the same shape and size as the first voxel on each first voxel in the important monitoring area,
The score setting unit sets a score for each of a plurality of surfaces of each third voxel within the focused monitoring area,
The optimal placement search unit is configured to select, within the important monitoring area, a value corresponding to the number of points set for the second voxels included in any one of the plurality of imaging ranges and any one of the plurality of imaging ranges. outside the focused monitoring area, the number of the first voxels included in any one of the plurality of imaging ranges calculating the score by counting
A program characterized by a monitoring region setting unit arranging a plurality of first voxels having a predetermined shape and size in a virtual monitoring region;
an important monitoring area setting unit setting an important monitoring area, which is an area to be monitored intensively, within the monitoring area;
an optimum placement search unit that changes at least one of the positions and orientations of at least some of the plurality of imaging devices virtually arranged in the monitoring area to determine the plurality of imaging ranges of the plurality of imaging devices; By repeating the process of calculating a score by counting the values obtained from the space in which the first voxel included in any is arranged, the score is maximized under a predetermined condition, Explore placement of multiple imaging devices,
The focused monitoring area setting unit generates a plurality of second voxels by dividing each first voxel in the focused monitoring area,
The optimal placement search unit counts the number of the second voxels included in any one of the plurality of imaging ranges in the important monitoring area, thereby determining the first voxels in the important monitoring area. calculating the score such that the value obtained from the space in which the voxel is arranged is higher than the value obtained from the space in which the first voxel is arranged outside the focused monitoring area;
An information processing method characterized by: a monitoring region setting unit arranging a plurality of first voxels having a predetermined shape and size in a virtual monitoring region;
an important monitoring area setting unit setting an important monitoring area, which is an area to be monitored intensively, within the monitoring area;
an optimum placement search unit that changes at least one of the positions and orientations of at least some of the plurality of imaging devices virtually arranged in the monitoring area to determine the plurality of imaging ranges of the plurality of imaging devices; By repeating the process of calculating a score by counting the values obtained from the space in which the first voxel included in any is arranged, the score is maximized under a predetermined condition, Explore placement of multiple imaging devices,
The focused monitoring area setting unit superimposes a second voxel having the same shape and size as the first voxel on each first voxel in the focused monitoring area,
The optimal placement search unit counts the number of the first voxels and the second voxels included in any one of the plurality of imaging ranges in the important monitoring area, thereby determining the important monitoring area. calculating the score such that a value obtained from a space in which the first voxel is arranged within the area is higher than a value obtained from a space in which the first voxel is arranged outside the focused monitoring area. thing
An information processing method characterized by: a monitoring region setting unit arranging a plurality of first voxels having a predetermined shape and size in a virtual monitoring region;
an important monitoring area setting unit setting an important monitoring area, which is an area to be monitored intensively, within the monitoring area;
an optimum placement search unit that changes at least one of the positions and orientations of at least some of the plurality of imaging devices virtually arranged in the monitoring area to determine the plurality of imaging ranges of the plurality of imaging devices; By repeating the process of calculating a score by counting the values obtained from the space in which the first voxel included in any is arranged, the score is maximized under a predetermined condition, Explore placement of multiple imaging devices,
a score setting unit generating a second voxel by setting a score for each of a plurality of surfaces of each first voxel in the focused monitoring area;
The optimal placement search unit counts a value corresponding to the number of points set for the second voxels included in one of the plurality of imaging ranges within the focused monitoring area, and Then, the score is calculated by counting the number of the first voxels included in any of the plurality of imaging ranges.
An information processing method characterized by: a monitoring region setting unit arranging a plurality of first voxels having a predetermined shape and size in a virtual monitoring region;
an important monitoring area setting unit setting an important monitoring area, which is an area to be monitored intensively, within the monitoring area;
an optimum placement search unit that changes at least one of the positions and orientations of at least some of the plurality of imaging devices virtually arranged in the monitoring area to determine the plurality of imaging ranges of the plurality of imaging devices; By repeating the process of calculating a score by counting the values obtained from the space in which the first voxel included in any is arranged, the score is maximized under a predetermined condition, Explore placement of multiple imaging devices,
a score setting unit generating a second voxel by setting a score for each of a plurality of surfaces of each first voxel in the focused monitoring area;
The important monitoring area setting unit superimposes a third voxel having the same shape and size as the first voxel on each first voxel in the important monitoring area,
The score setting unit sets a score for each of a plurality of surfaces of each third voxel within the focused monitoring area,
The optimal placement search unit is configured to select, within the important monitoring area, a value corresponding to the number of points set for the second voxels included in any one of the plurality of imaging ranges and any one of the plurality of imaging ranges. outside the focused monitoring area, the number of the first voxels included in any one of the plurality of imaging ranges calculating the score by counting
An information processing method characterized by: a monitoring region setting unit that arranges a plurality of first voxels having a predetermined shape and size in a virtual monitoring region;
an important monitoring area setting unit that sets an important monitoring area, which is an area to be monitored intensively, within the monitoring area, and arranges one or more second voxels in the first voxels of the important monitoring area;
Counting values obtained from a space in which the first voxel and the second voxel included in any of a plurality of imaging ranges of a plurality of imaging devices arranged within the monitoring area are arranged. an optimal arrangement search unit that calculates a score in and searches for an arrangement of the plurality of imaging devices that maximizes the score under a predetermined condition,
The optimal placement search unit determines a value obtained from a space in which the first voxels are placed within the focused monitoring area from a value obtained from a space outside the focused monitoring area in which the first voxels are placed. calculating the score so that
An information processing device characterized by: a monitoring region setting unit that arranges a plurality of first voxels having a predetermined shape and size in a virtual monitoring region;
an important monitoring area setting unit for setting an important monitoring area, which is an area to be monitored intensively, within the monitoring area;
calculating a score by counting values obtained from a space in which the first voxels included in any of a plurality of imaging ranges of a plurality of imaging devices arranged in the monitoring region are arranged; an optimal placement search unit that searches for a placement of the plurality of imaging devices that maximizes the score under a predetermined condition;
a score setting unit that generates a second voxel by setting a score for each of a plurality of surfaces of each of the first voxels in the focused monitoring area;
The optimal placement search unit counts a value corresponding to the number of points set for the second voxels included in one of the plurality of imaging ranges within the focused monitoring area, and Then, the score is calculated by counting the number of the first voxels included in any of the plurality of imaging ranges.
An information processing device characterized by: a monitoring region setting unit that arranges a plurality of first voxels having a predetermined shape and size in a virtual monitoring region;
an important monitoring area setting unit for setting an important monitoring area, which is an area to be monitored intensively, within the monitoring area;
calculating a score by counting values obtained from a space in which the first voxels included in any of a plurality of imaging ranges of a plurality of imaging devices arranged in the monitoring region are arranged; an optimal placement search unit that searches for a placement of the plurality of imaging devices that maximizes the score under a predetermined condition;
a score setting unit that generates a second voxel by setting a score for each of a plurality of surfaces of each of the first voxels in the focused monitoring area;
The important monitoring area setting unit superimposes a third voxel having the same shape and size as the first voxel on each first voxel in the important monitoring area,
The score setting unit sets a score for each of a plurality of surfaces of each third voxel within the focused monitoring area,
The optimal placement search unit is configured to select, within the important monitoring area, a value corresponding to the number of points set for the second voxels included in any one of the plurality of imaging ranges and any one of the plurality of imaging ranges. outside the focused monitoring area, the number of the first voxels included in any one of the plurality of imaging ranges calculating the score by counting
An information processing device characterized by: the computer,
a monitoring region setting unit that arranges a plurality of first voxels having a predetermined shape and size in a virtual monitoring region;
an important monitoring area setting unit for setting an important monitoring area, which is an area to be monitored intensively, within the monitoring area, and arranging one or more second voxels in the first voxels of the important monitoring area; ,
Counting values obtained from a space in which the first voxel and the second voxel included in any of a plurality of imaging ranges of a plurality of imaging devices arranged within the monitoring area are arranged. to calculate the score, and function as an optimum arrangement search unit that searches for the arrangement of the plurality of imaging devices that maximizes the score under a predetermined condition,
The optimal placement search unit determines a value obtained from a space in which the first voxels are placed within the focused monitoring area from a value obtained from a space outside the focused monitoring area in which the first voxels are placed. calculating the score so that
A program characterized by the computer,
a monitoring region setting unit that arranges a plurality of first voxels having a predetermined shape and size in a virtual monitoring region;
an important monitoring area setting unit for setting an important monitoring area, which is an area to be monitored intensively, within the monitoring area;
calculating a score by counting values obtained from a space in which the first voxels included in any of a plurality of imaging ranges of a plurality of imaging devices arranged in the monitoring region are arranged; an optimal placement search unit that searches for a placement of the plurality of imaging devices that maximizes the score under predetermined conditions;
Functioning as a score setting unit that generates a second voxel by setting a score for each of a plurality of surfaces of each first voxel in the focused monitoring area,
The optimal placement search unit counts a value corresponding to the number of points set for the second voxels included in one of the plurality of imaging ranges within the focused monitoring area, and Then, the score is calculated by counting the number of the first voxels included in any of the plurality of imaging ranges.
A program characterized by the computer,
a monitoring region setting unit that arranges a plurality of first voxels having a predetermined shape and size in a virtual monitoring region;
an important monitoring area setting unit for setting an important monitoring area, which is an area to be monitored intensively, within the monitoring area;
calculating a score by counting values obtained from a space in which the first voxels included in any of a plurality of imaging ranges of a plurality of imaging devices arranged in the monitoring region are arranged; an optimal placement search unit that searches for a placement of the plurality of imaging devices that maximizes the score under predetermined conditions;
Functioning as a score setting unit that generates a second voxel by setting a score for each of a plurality of surfaces of each first voxel in the focused monitoring area,
The important monitoring area setting unit superimposes a third voxel having the same shape and size as the first voxel on each first voxel in the important monitoring area,
The score setting unit sets a score for each of a plurality of surfaces of each third voxel within the focused monitoring area,
The optimal placement search unit is configured to select, within the important monitoring area, a value corresponding to the number of points set for the second voxels included in any one of the plurality of imaging ranges and any one of the plurality of imaging ranges. outside the focused monitoring area, the number of the first voxels included in any one of the plurality of imaging ranges calculating the score by counting
A program characterized by a monitoring region setting unit arranging a plurality of first voxels having a predetermined shape and size in a virtual monitoring region;
An important monitoring area setting unit sets an important monitoring area, which is an area to be intensively monitored, within the monitoring area, and arranges one or more second voxels in the first voxels of the important monitoring area. ,
An optimum placement search unit is obtained from the space in which the first voxels and the second voxels included in any of a plurality of imaging ranges of a plurality of imaging devices arranged within the monitoring area are arranged. calculating a score by counting each value, and searching for an arrangement of the plurality of imaging devices that maximizes the score under a predetermined condition;
The optimal placement search unit determines a value obtained from a space in which the first voxels are placed within the focused monitoring area from a value obtained from a space outside the focused monitoring area in which the first voxels are placed. calculating the score so that
An information processing method characterized by: a monitoring region setting unit arranging a plurality of first voxels having a predetermined shape and size in a virtual monitoring region;
an important monitoring area setting unit setting an important monitoring area, which is an area to be monitored intensively, within the monitoring area;
By counting the value obtained from the space in which the first voxels included in one of the plurality of imaging ranges of the plurality of imaging devices arranged in the monitoring area are arranged, by the optimum arrangement search unit calculating a score and searching for an arrangement of the plurality of imaging devices that maximizes the score under a predetermined condition;
An information processing method in which a score setting unit generates a second voxel by setting a score for each of a plurality of surfaces of each first voxel in the focused monitoring area,
The optimal placement search unit counts a value corresponding to the number of points set for the second voxels included in one of the plurality of imaging ranges within the focused monitoring area, and Then, the score is calculated by counting the number of the first voxels included in any of the plurality of imaging ranges.
An information processing method characterized by: a monitoring region setting unit arranging a plurality of first voxels having a predetermined shape and size in a virtual monitoring region;
an important monitoring area setting unit setting an important monitoring area, which is an area to be monitored intensively, within the monitoring area;
By counting the value obtained from the space in which the first voxels included in one of the plurality of imaging ranges of the plurality of imaging devices arranged in the monitoring area are arranged, by the optimum arrangement search unit calculating a score and searching for an arrangement of the plurality of imaging devices that maximizes the score under a predetermined condition;
An information processing method in which a score setting unit generates a second voxel by setting a score for each of a plurality of surfaces of each first voxel in the focused monitoring area,
The important monitoring area setting unit superimposes a third voxel having the same shape and size as the first voxel on each first voxel in the important monitoring area,
The score setting unit sets a score for each of a plurality of surfaces of each third voxel within the focused monitoring area,
The optimal placement search unit is configured to select, within the important monitoring area, a value corresponding to the number of points set for the second voxels included in any one of the plurality of imaging ranges and any one of the plurality of imaging ranges. outside the focused monitoring area, the number of the first voxels included in any one of the plurality of imaging ranges calculating the score by counting
An information processing method characterized by:

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